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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: BERT_with_preprocessing_grid_search |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# BERT_with_preprocessing_grid_search |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8836 |
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- Precision: 0.8262 |
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- Recall: 0.8258 |
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- F1: 0.8249 |
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- Accuracy: 0.8724 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 1.047 | 1.0 | 510 | 0.6171 | 0.7493 | 0.8057 | 0.7716 | 0.8336 | |
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| 0.4348 | 2.0 | 1020 | 0.4954 | 0.8056 | 0.8646 | 0.8296 | 0.8714 | |
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| 0.2818 | 3.0 | 1530 | 0.6252 | 0.8181 | 0.8323 | 0.8212 | 0.8660 | |
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| 0.1793 | 4.0 | 2040 | 0.7381 | 0.8216 | 0.8258 | 0.8227 | 0.8733 | |
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| 0.1356 | 5.0 | 2550 | 0.8601 | 0.8161 | 0.8219 | 0.8165 | 0.8660 | |
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| 0.1023 | 6.0 | 3060 | 0.8526 | 0.8363 | 0.8299 | 0.8307 | 0.8758 | |
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| 0.0944 | 7.0 | 3570 | 0.8459 | 0.8234 | 0.8298 | 0.8251 | 0.8729 | |
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| 0.0631 | 8.0 | 4080 | 0.8519 | 0.8212 | 0.8325 | 0.8252 | 0.8714 | |
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| 0.0602 | 9.0 | 4590 | 0.8756 | 0.8200 | 0.8267 | 0.8226 | 0.8719 | |
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| 0.0532 | 10.0 | 5100 | 0.8836 | 0.8262 | 0.8258 | 0.8249 | 0.8724 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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